DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) were submitted on 02/10/25 and 02/19/25. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 16-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Ranganath et al. (US 20200242341 A1) (Ranganath).
Regarding claim 16, Ranganath discloses a method (See Fig. 6), comprising:
capturing face images of people at a particular location during a current period (See Figs. 1 and 6; para. 22);
performing, for each of the face images captured during the current period, face recognition using a value of a decision threshold to make a determination whether the captured face image and a stored face image in a database of stored face images are of the same person, wherein a positive determination indicates that the captured face image and the stored face image are of the same person (See Fig. 6; para. 41);
calculating a current positive determination rate for the face images captured during the current period (See para. 41; e.g. variety of parameters used to adjust thresholds); and
automatically adjusting the value of the decision threshold for performing the face recognition during a subsequent period following the current period (e.g. the next guest scan), wherein the value of the decision threshold is increased for performing the face recognition during the subsequent period in response to the current positive determination rate being greater than a target positive determination rate during the current period (e.g. when fraud is more likely to occur during a time period), and wherein the value of the decision threshold is decreased for performing the face recognition during the subsequent period in response to the current positive determination rate being less than the target positive determination rate during the current period (e.g. in order to insure adequate throughput) (See para. 41; e.g. adjusting the thresholds up and/or down based on a variety of thresholds).
Regarding claim 17, The method of claim 16, the operations further comprising: repeating the operations during each of a plurality of sequential periods (See Figs. 1 and 6; the process repeats for each guest).
Regarding claim 18, The method of claim 16, wherein the positive determination indicates that the captured face image is of the same person as in any of the stored face images in the database (e.g. database 14) (See para. 41).
Regarding claim 19, The method of claim 16, wherein increasing the value of the decision threshold requires greater similarity between face two images to determine a positive match (See Fig. 6; para. 41; e.g. higher score between two images).
Regarding claim 20, The method of claim 16, wherein decreasing the value of the decision threshold requires less similarity between the captured face image and the stored face image to determine a positive match (See Fig. 6; para. 41; e.g. lowering the threshold results in lower scores between two images to pass).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-5, 7-9, and 11-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranganath et al. (US 20200242341 A1) (Ranganath) in view of Ganong et al. (US 9639740 B2) (Ganong).
Regarding claim 1, Ranganath discloses a facial recognition system that (See Figs. 1 and 6):
capturing face images of people at a particular location during a current period (See Figs. 1 and 6; para. 22);
performing, for each of the face images captured during the current period, face recognition using a value of a decision threshold to make a determination whether the captured face image and a stored face image in a database of stored face images are of the same person, wherein a positive determination indicates that the captured face image and the stored face image are of the same person (See Fig. 6; para. 41);
calculating a current positive determination rate for the face images captured during the current period (See para. 41; e.g. variety of parameters used to adjust thresholds); and
automatically adjusting the value of the decision threshold for performing the face recognition during a subsequent period following the current period (e.g. the next guest scan), wherein the value of the decision threshold is increased for performing the face recognition during the subsequent period in response to the current positive determination rate being greater than a target positive determination rate during the current period (e.g. when fraud is more likely to occur during a time period), and wherein the value of the decision threshold is decreased for performing the face recognition during the subsequent period in response to the current positive determination rate being less than the target positive determination rate during the current period (e.g. in order to insure adequate throughput) (See para. 41; e.g. adjusting the thresholds up and/or down based on a variety of thresholds).
However, Ranganath does not explicitly disclose a computer program product comprising a non-volatile computer readable medium and non- transitory program instructions embodied therein, the program instructions being configured to be executable by a processor to cause the processor to perform operations.
Ganong discloses a facial recognition system. Ganong discloses a computer program product comprising a non-volatile computer readable medium and non- transitory program instructions embodied therein, the program instructions being configured to be executable by a processor to cause the processor to perform operations (See col. 5 lines 13-63 and col. 45 line 61 – col. 46 line 28).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the facial recognition system on a computer program product of Ganong with the facial recognition system as disclosed by Ranganath in order to easily implement the operations across different systems (See Ganong col. 46 lines 23-28).
Regarding claim 2, The computer program product of claim 1, the operations further comprising: repeating the operations during each of a plurality of sequential periods (See Ranganath Figs. 1 and 6; the process repeats for each guest).
Regarding claim 3, The computer program product of claim 1, wherein the positive determination indicates that the captured face image is of the same person as in any of the stored face images in the database (e.g. database 14) (See Ranganath para. 41).
Regarding claim 4, The computer program product of claim 1, wherein increasing the value of the decision threshold requires greater similarity between the captured face image and the stored face image to determine a positive match (See Ranganath Fig. 6; para. 41; e.g. higher score between two images).
Regarding claim 5, The computer program product of claim 1, wherein decreasing the value of the decision threshold requires less similarity between the captured face image and the stored face image to determine a positive match (See Ranganath Fig. 6; para. 41; e.g. lowering the threshold results in lower scores between two images to pass).
Regarding claim 7, The computer program product of claim 1, wherein the operation of automatically adjusting the value of the decision threshold for performing face recognition during the subsequent period following the current period includes:
incrementally adjusting the value of the decision threshold by a predetermined amount (See Ranganath Fig. 6; para. 41; e.g. predetermined amounts).
Regarding claim 8, The computer program product of claim 1, wherein each of the periods is defined by an amount of time (e.g. match timer) or a number of determinations whether the captured face image is of the same person as one of the stored face images in the database of stored face images (See Ranganath paras. 41-43).
Regarding claim 9, The computer program product of claim 1, wherein the current period ends and the subsequent period begins in response to a difference between the current positive determination rate and the target positive determination rate exceeding a maximum threshold (e.g. variety of parameters used to adjust thresholds not being and/or being met) (See Ranganath paras. 41-43).
Regarding claim 11, The computer program product of claim 1, wherein the operation of capturing face images of people at the particular location during the current period includes: receiving the face images from a camera mounted in the particular location (e.g. theme parks) (See Ranganath Fig. 1; para. 21-30).
Regarding claim 12, The computer program product of claim 1, wherein the operation of performing, for each of the face images captured during the current period, face recognition using a value of a decision threshold to make a determination whether the captured face image and a stored face image in a database of stored face images are of the same person includes:
submitting the captured face image, one or more of the stored face images in the database, and the value of the decision threshold to a face recognition system (See Ranganath Figs. 1, 5, 6; paras. 41-43); and
receiving the determination whether the captured face image and any of the one or more of the stored face images in a database are of the same person from the face recognition system (See Ranganath Figs. 1, 5, 6; paras. 41-43).
Regarding claim 13, The computer program product of claim 1, wherein the target positive determination rate is a known value based on previous experience (e.g. history of fraud or overrides) (See Ranganath para. 41).
Regarding claim 14, The computer program product of claim 1, wherein the target positive determination rate is designated according to a capacity to process positive determinations (e.g. adequate throughput) (See Ranganath paras. 41-43).
Regarding claim 15, The computer program product of claim 1, wherein the automatic adjusting of the value of the decision threshold adapts to changes in environmental conditions affecting quality of the face images captured at the particular location (See Ranganath Fig. 7; paras. 62-63).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranganath et al. (US 20200242341 A1) (Ranganath) in view of Ganong et al. (US 9639740 B2) (Ganong) as applied to claims 1-5, 7-9, and 11-15 above, and further in view of Dahlkamp et al. (US 20210383100 A1) (Dahlkamp).
Regarding claim 6, Ranganath in view of Ganong discloses wherein the operation of performing, for each of the face images captured during the current period, face recognition includes:
calculating, for each of the face images captured during the current period, an amount of difference (similarity) between a face print for the captured face image with a face print for each of a plurality of stored face images (See Ranganath para. 41); and
making a positive determination for the captured face image in response to the calculated amount of difference (similarity) being less (more) than the value of the decision threshold (See Ranganath para. 41).
However, Ranganath in view of Ganong does not explicitly disclose calculating a difference between faces and making a positive determination when the difference is less than a threshold.
Dahlkamp discloses a facial recognition system. Dahlkamp discloses that the system is able to perform facial recognition by either using similarity or differences when determining a score for matching faces (See para. 46).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the facial recognition system of Dahlkamp with the facial recognition system as disclosed by Ranganath in view of Ganong in order to accurately recognize faces (See Dahlkamp para. 2).
The claimed difference score vs similarity score is an obvious matter of design choice because the prior art teaches the same general function, and applicant has not shown that the claimed feature is critical or produces an unexpected result. See In re Kuhle, 526 F.2d 553 (CCPA 1975); In re Gal, 980 F.2d 717 (Fed. Cir. 1992).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranganath et al. (US 20200242341 A1) (Ranganath) in view of Ganong et al. (US 9639740 B2) (Ganong) as applied to claims 1-5, 7-9, and 11-15 above, and further in view of Tran et al. “High Performance DeepFake Video Detection on CNN-Based with Attention Target-Specific Regions and Manual Distillation Extraction” (IDS) (Tran).
Regarding claim 10, Ranganath in view of Ganong discloses calculating scores and other parameters (See Ranganath paras. 39 and 41). However, Ranganath in view of Ganong does not explicitly disclose wherein the operation of calculating the current positive determination rate for the face images captured during the current period includes:
identifying a total number of the determinations are made during the current period;
identifying a number of positive determinations made during the current period, wherein the current positive determination rate is the number of positive determinations divided by the total number of determinations.
Tran discloses facial detection system Tran discloses calculating an accuracy wherein:
identifying a total number of the determinations are made during the current period (e.g. total number of predictions);
identifying a number of positive determinations made during the current period (e.g. correct predictions), wherein the current positive determination rate is the number of positive determinations divided by the total number of determinations (e.g. number of correct positions/total number of predictions) (See page 9 equation 10).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the facial detection system of Tran with the facial recognition system as disclosed by Ranganath in view of Ganong in order to measure how well the system is working (See Tran page 9 para. 8).
The claimed determinations vs predictions is an obvious matter of design choice because the prior art teaches the same general function, and applicant has not shown that the claimed feature is critical or produces an unexpected result. See In re Kuhle, 526 F.2d 553 (CCPA 1975); In re Gal, 980 F.2d 717 (Fed. Cir. 1992).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Joseph G Ustaris whose telephone number is (571)272-7383. The examiner can normally be reached 9-5pm M-Th.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Colleen A Fauz can be reached at 571-272-1667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOSEPH G USTARIS/Supervisory Patent Examiner, Art Unit 2483
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